Given a dataset P, a k-means query returns k points in space (called centers), such that the average squared distance between each point in P and its nearest center is minimized. S...
Zhenjie Zhang, Yin Yang, Anthony K. H. Tung, Dimit...
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...
Methods based on local, viewpoint invariant features have proven capable of recognizing objects in spite of viewpoint changes, occlusion and clutter. However, these approaches fail...
Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Goo...
Design-time decisions can often only cover certain scenarios and fail in efficiency when hard-to-predict system scenarios occur. This drives the development of run-time adaptive s...